{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f355316a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    }
   ],
   "source": [
    "from gernerate_data import load_clas_seg_data\n",
    "import tensorflow as tf\n",
    "from sklearn.metrics import classification_report, auc, roc_curve\n",
    "from keras.utils.np_utils import *\n",
    "from keras.callbacks import LearningRateScheduler\n",
    "from models.shareMoreLayers_sobel import create_pair_model\n",
    "from sklearn.preprocessing import LabelBinarizer, label_binarize\n",
    "from utils.losses import dice_coef_loss, dice_coef, dice_p_bce, dice_p_focal, tversky_loss, focal_loss, focal_tversky, \\\n",
    "    p_r_f1_iou, generalized_dice_coeff, generalized_dice_loss\n",
    "from keras.losses import categorical_crossentropy, mean_squared_error, binary_crossentropy\n",
    "from keras.callbacks import ReduceLROnPlateau, ModelCheckpoint, EarlyStopping, CSVLogger\n",
    "from keras.optimizers import Adam\n",
    "import matplotlib.pyplot as plt\n",
    "import keras.backend as K\n",
    "import utils_paths\n",
    "import numpy as np\n",
    "import pickle\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3ed814ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------------ Preparing model ------------------------------------------------\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-21 01:12:21.669169: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
      "2022-03-21 01:12:21.705301: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2200095000 Hz\n",
      "2022-03-21 01:12:21.709144: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x4666460 executing computations on platform Host. Devices:\n",
      "2022-03-21 01:12:21.709235: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>\n",
      "2022-03-21 01:12:22.346187: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x46e2d20 executing computations on platform CUDA. Devices:\n",
      "2022-03-21 01:12:22.346278: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): Tesla V100-PCIE-32GB, Compute Capability 7.0\n",
      "2022-03-21 01:12:22.347185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties: \n",
      "name: Tesla V100-PCIE-32GB major: 7 minor: 0 memoryClockRate(GHz): 1.38\n",
      "pciBusID: 0000:85:00.0\n",
      "totalMemory: 31.72GiB freeMemory: 31.31GiB\n",
      "2022-03-21 01:12:22.347225: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0\n",
      "2022-03-21 01:12:22.349340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2022-03-21 01:12:22.349383: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0 \n",
      "2022-03-21 01:12:22.349393: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N \n",
      "2022-03-21 01:12:22.350211: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 30458 MB memory) -> physical GPU (device: 0, name: Tesla V100-PCIE-32GB, pci bus id: 0000:85:00.0, compute capability: 7.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "cls_input (InputLayer)          (None, 224, 224, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "seg_input (InputLayer)          (None, 224, 224, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lambda_1 (Lambda)               (None, 224, 224, 3)  0           cls_input[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_2 (Lambda)               (None, 224, 224, 3)  0           seg_input[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_1 (Multiply)           (None, 224, 224, 3)  0           cls_input[0][0]                  \n",
      "                                                                 lambda_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_2 (Multiply)           (None, 224, 224, 3)  0           seg_input[0][0]                  \n",
      "                                                                 lambda_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "share_conv1_1 (Conv2D)          (None, 224, 224, 64) 1792        multiply_1[0][0]                 \n",
      "                                                                 multiply_2[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 224, 224, 64) 256         share_conv1_1[0][0]              \n",
      "                                                                 share_conv1_1[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 224, 224, 64) 0           batch_normalization_1[0][0]      \n",
      "                                                                 batch_normalization_1[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2 (Conv2D)           (None, 224, 224, 64) 36928       activation_1[0][0]               \n",
      "                                                                 activation_1[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 224, 224, 64) 256         block1_conv2[0][0]               \n",
      "                                                                 block1_conv2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 224, 224, 64) 0           batch_normalization_2[0][0]      \n",
      "                                                                 batch_normalization_2[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 112, 112, 64) 0           activation_2[0][0]               \n",
      "                                                                 activation_2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv1 (Conv2D)           (None, 112, 112, 128 73856       max_pooling2d_1[0][0]            \n",
      "                                                                 max_pooling2d_1[1][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 112, 112, 128 512         block2_conv1[0][0]               \n",
      "                                                                 block2_conv1[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 112, 112, 128 0           batch_normalization_3[0][0]      \n",
      "                                                                 batch_normalization_3[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv2 (Conv2D)           (None, 112, 112, 128 147584      activation_3[0][0]               \n",
      "                                                                 activation_3[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 112, 112, 128 512         block2_conv2[0][0]               \n",
      "                                                                 block2_conv2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 112, 112, 128 0           batch_normalization_4[0][0]      \n",
      "                                                                 batch_normalization_4[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 56, 56, 128)  0           activation_4[0][0]               \n",
      "                                                                 activation_4[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "block3_conv1 (Conv2D)           (None, 56, 56, 256)  295168      max_pooling2d_2[0][0]            \n",
      "                                                                 max_pooling2d_2[1][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 56, 56, 256)  1024        block3_conv1[0][0]               \n",
      "                                                                 block3_conv1[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 56, 56, 256)  0           batch_normalization_5[0][0]      \n",
      "                                                                 batch_normalization_5[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block3_conv2 (Conv2D)           (None, 56, 56, 256)  590080      activation_5[0][0]               \n",
      "                                                                 activation_5[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 56, 56, 256)  1024        block3_conv2[0][0]               \n",
      "                                                                 block3_conv2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 56, 56, 256)  0           batch_normalization_6[0][0]      \n",
      "                                                                 batch_normalization_6[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block3_conv3 (Conv2D)           (None, 56, 56, 256)  590080      activation_6[0][0]               \n",
      "                                                                 activation_6[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 56, 56, 256)  1024        block3_conv3[0][0]               \n",
      "                                                                 block3_conv3[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 56, 56, 256)  0           batch_normalization_7[0][0]      \n",
      "                                                                 batch_normalization_7[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 28, 28, 256)  0           activation_7[0][0]               \n",
      "                                                                 activation_7[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv1 (Conv2D)           (None, 28, 28, 512)  1180160     max_pooling2d_3[0][0]            \n",
      "                                                                 max_pooling2d_3[1][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 28, 28, 512)  2048        block4_conv1[0][0]               \n",
      "                                                                 block4_conv1[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 28, 28, 512)  0           batch_normalization_8[0][0]      \n",
      "                                                                 batch_normalization_8[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv2 (Conv2D)           (None, 28, 28, 512)  2359808     activation_8[0][0]               \n",
      "                                                                 activation_8[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 28, 28, 512)  2048        block4_conv2[0][0]               \n",
      "                                                                 block4_conv2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 28, 28, 512)  0           batch_normalization_9[0][0]      \n",
      "                                                                 batch_normalization_9[1][0]      \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv3 (Conv2D)           (None, 28, 28, 512)  2359808     activation_9[0][0]               \n",
      "                                                                 activation_9[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 28, 28, 512)  2048        block4_conv3[0][0]               \n",
      "                                                                 block4_conv3[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 28, 28, 512)  0           batch_normalization_10[0][0]     \n",
      "                                                                 batch_normalization_10[1][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 14, 14, 512)  0           activation_10[0][0]              \n",
      "                                                                 activation_10[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block5_conv1 (Conv2D)           (None, 14, 14, 512)  2359808     max_pooling2d_4[0][0]            \n",
      "                                                                 max_pooling2d_4[1][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 14, 14, 512)  2048        block5_conv1[0][0]               \n",
      "                                                                 block5_conv1[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 14, 14, 512)  0           batch_normalization_11[0][0]     \n",
      "                                                                 batch_normalization_11[1][0]     \n",
      "__________________________________________________________________________________________________\n",
      "block5_conv2 (Conv2D)           (None, 14, 14, 512)  2359808     activation_11[0][0]              \n",
      "                                                                 activation_11[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 14, 14, 512)  2048        block5_conv2[0][0]               \n",
      "                                                                 block5_conv2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 14, 14, 512)  0           batch_normalization_12[0][0]     \n",
      "                                                                 batch_normalization_12[1][0]     \n",
      "__________________________________________________________________________________________________\n",
      "block5_conv3 (Conv2D)           (None, 14, 14, 512)  2359808     activation_12[0][0]              \n",
      "                                                                 activation_12[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 14, 14, 512)  2048        block5_conv3[0][0]               \n",
      "                                                                 block5_conv3[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 14, 14, 512)  0           batch_normalization_13[0][0]     \n",
      "                                                                 batch_normalization_13[1][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_1 (Conv2DTrans (None, 28, 28, 512)  1049088     activation_13[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 28, 28, 512)  2048        conv2d_transpose_1[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 28, 28, 512)  0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 28, 28, 1024) 0           activation_14[0][0]              \n",
      "                                                                 activation_10[1][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 28, 28, 512)  4719104     concatenate_1[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_15 (BatchNo (None, 28, 28, 512)  2048        conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 28, 28, 512)  0           batch_normalization_15[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 28, 28, 512)  2359808     activation_15[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_16 (BatchNo (None, 28, 28, 512)  2048        conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 28, 28, 512)  0           batch_normalization_16[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_2 (Conv2DTrans (None, 56, 56, 256)  524544      activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_17 (BatchNo (None, 56, 56, 256)  1024        conv2d_transpose_2[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 56, 56, 256)  0           batch_normalization_17[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_2 (Concatenate)     (None, 56, 56, 512)  0           activation_17[0][0]              \n",
      "                                                                 activation_7[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 56, 56, 256)  1179904     concatenate_2[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_18 (BatchNo (None, 56, 56, 256)  1024        conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 56, 56, 256)  0           batch_normalization_18[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 56, 56, 256)  590080      activation_18[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_19 (BatchNo (None, 56, 56, 256)  1024        conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 56, 56, 256)  0           batch_normalization_19[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_3 (Conv2DTrans (None, 112, 112, 128 131200      activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_20 (BatchNo (None, 112, 112, 128 512         conv2d_transpose_3[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 112, 112, 128 0           batch_normalization_20[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_3 (Concatenate)     (None, 112, 112, 256 0           activation_20[0][0]              \n",
      "                                                                 activation_4[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 112, 112, 128 295040      concatenate_3[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_21 (BatchNo (None, 112, 112, 128 512         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 112, 112, 128 0           batch_normalization_21[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 112, 112, 128 147584      activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_22 (BatchNo (None, 112, 112, 128 512         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 112, 112, 128 0           batch_normalization_22[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_4 (Conv2DTrans (None, 224, 224, 64) 32832       activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_23 (BatchNo (None, 224, 224, 64) 256         conv2d_transpose_4[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 224, 224, 64) 0           batch_normalization_23[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_4 (Concatenate)     (None, 224, 224, 128 0           activation_23[0][0]              \n",
      "                                                                 activation_2[1][0]               \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_5 (MaxPooling2D)  (None, 7, 7, 512)    0           activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 224, 224, 64) 73792       concatenate_4[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "cls_flatten (Flatten)           (None, 25088)        0           max_pooling2d_5[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_24 (BatchNo (None, 224, 224, 64) 256         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "cls_dense_0 (Dense)             (None, 64)           1605696     cls_flatten[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 224, 224, 64) 0           batch_normalization_24[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "cls_act_3 (Activation)          (None, 64)           0           cls_dense_0[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 224, 224, 64) 36928       activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "cls_dropout (Dropout)           (None, 64)           0           cls_act_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 224, 224, 64) 256         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "cls_dense_out (Dense)           (None, 2)            130         cls_dropout[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 224, 224, 64) 0           batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "classification_output (Activati (None, 2)            0           cls_dense_out[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "segmentation_output (Conv2D)    (None, 224, 224, 2)  1154        activation_25[0][0]              \n",
      "==================================================================================================\n",
      "Total params: 27,489,988\n",
      "Trainable params: 27,475,780\n",
      "Non-trainable params: 14,208\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "INIT_LR = 1e-3\n",
    "EPOCHS =300\n",
    "batch_size = 8\n",
    "depth = 3\n",
    "img_size = 224\n",
    "Name = \"shareLayer\"\n",
    "GPU = True\n",
    "target = (img_size, img_size)\n",
    "\n",
    "if GPU:\n",
    "    os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\"\n",
    "    os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"2\"\n",
    "\n",
    "\n",
    "    \n",
    "print(\"------------------------------------------------ Preparing model ------------------------------------------------\")\n",
    "model = create_pair_model(img_size, img_size, depth, nClasses=2)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7479810",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    {
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     "text": [
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      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (118).png\n",
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      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (239).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (384).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (384).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (305).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (305).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (287).png\n",
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      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (92).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (92).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (50).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (50).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (114).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (114).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (122).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (122).png\n",
      "dataset/Dataset_BUSI_AN/val/images/bengin_images/benign (429).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/bengin_masks/benign (429).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (175).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (175).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (195).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (195).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (163).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (163).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (103).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (103).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (38).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (38).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (59).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (59).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (129).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (129).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (39).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (39).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (118).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (118).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (172).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (172).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (189).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (189).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (80).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (80).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (5).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (5).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (139).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (139).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (34).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (34).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (49).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (49).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (119).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (119).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (14).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (14).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (177).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (177).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (201).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (201).png\n",
      "dataset/Dataset_BUSI_AN/val/images/malignant_images/malignant (160).png\n",
      "dataset/Dataset_BUSI_AN/val/masks/malignant_masks/malignant (160).png\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (57).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (57).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (220).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (220).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (103).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (103).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (150).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (150).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (84).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (84).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (88).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (88).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (391).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (391).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (408).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (408).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (147).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (147).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (142).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (142).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (425).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (425).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (48).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (48).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (316).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (316).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (140).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (364).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (167).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (321).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (21).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (15).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (15).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (388).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (388).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (299).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (153).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (136).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (297).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (349).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (155).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (222).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (222).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (119).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (51).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (51).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (218).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (38).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (154).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (231).png\n",
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      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (221).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (221).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (372).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (372).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (201).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (201).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (127).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (127).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (315).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (315).png\n",
      "dataset/Dataset_BUSI_AN/test/images/bengin_images/benign (187).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/bengin_masks/benign (187).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (20).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (20).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (191).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (191).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (45).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (45).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (106).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (106).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (171).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (171).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (65).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (65).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (18).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (18).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (86).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (86).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (112).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (112).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (44).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (44).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (136).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (136).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (146).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (146).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (149).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (149).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (170).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (170).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (74).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (74).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (121).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (121).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (72).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (72).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (190).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (190).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (131).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (131).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (123).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (123).png\n",
      "dataset/Dataset_BUSI_AN/test/images/malignant_images/malignant (200).png\n",
      "dataset/Dataset_BUSI_AN/test/masks/malignant_masks/malignant (200).png\n"
     ]
    }
   ],
   "source": [
    "# trainX_dir = 'dataset/LE/test/images/'\n",
    "trainX_dir = 'dataset/Dataset_BUSI_AN/train/images/'\n",
    "valX_dir = trainX_dir.replace('train', 'val')\n",
    "testX_dir = trainX_dir.replace('train', 'test')\n",
    "\n",
    "\n",
    "train_x,  train_c_y, train_s_y = load_clas_seg_data(trainX_dir, target)\n",
    "val_x, val_c_y, val_s_y = load_clas_seg_data(valX_dir, target)\n",
    "test_x, test_c_y, test_s_y = load_clas_seg_data(testX_dir, target)\n",
    "\n",
    "\n",
    "lb = LabelBinarizer()\n",
    "train_c_y = lb.fit_transform(train_c_y)\n",
    "val_c_y = lb.fit_transform(val_c_y)\n",
    "test_c_y = lb.fit_transform(test_c_y)\n",
    "train_c_y = to_categorical(train_c_y, 2)\n",
    "val_c_y = to_categorical(val_c_y, 2)\n",
    "test_c_y = to_categorical(test_c_y, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c6931d5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define callbacks\n",
    "csv_logger = CSVLogger(Name+'.log')\n",
    "\n",
    "reduce_lr = ReduceLROnPlateau(monitor='classification_output_loss', factor=0.3, patience=20, min_lr=1e-8, mode='auto', verbose=1)\n",
    "\n",
    "# checkpoint_period1 = ModelCheckpoint(Name + '-{epoch:03d}-{classification_output_acc:.4f}.h5',\n",
    "#                                      monitor='classification_output_acc', mode='auto', save_best_only='True')\n",
    "\n",
    "\n",
    "\n",
    "# define loss and compile the model\n",
    "\n",
    "opt = Adam(lr=INIT_LR, beta_1=0.9, beta_2=0.99, epsilon=1e-08, decay=0.01)\n",
    "\n",
    "def binary_crossentropy(y_true, y_pred):\n",
    "    e=1.0\n",
    "    return K.mean(-(y_true*K.log(y_pred+K.epsilon())+\n",
    "                    e*(1-y_true)*K.log(1-y_pred+K.epsilon())),\n",
    "                  axis=-1)\n",
    "\n",
    "def tversky(y_true, y_pred, smooth=1):\n",
    "    y_true_pos = K.flatten(y_true)\n",
    "    y_pred_pos = K.flatten(y_pred)\n",
    "    true_pos = K.sum(y_true_pos * y_pred_pos)\n",
    "    false_neg = K.sum(y_true_pos * (1 - y_pred_pos))\n",
    "    false_pos = K.sum((1 - y_true_pos) * y_pred_pos)\n",
    "    alpha = 0.5\n",
    "    return (true_pos + smooth) / (true_pos + alpha * false_neg + (1 - alpha) * false_pos + smooth)\n",
    "\n",
    "def tversky_loss(y_true, y_pred):\n",
    "    return 1 - tversky(y_true, y_pred)\n",
    "\n",
    "\n",
    "from keras.losses import categorical_crossentropy\n",
    "\n",
    "model.compile(loss={'segmentation_output': 'categorical_crossentropy', \"classification_output\": binary_crossentropy},\n",
    "              loss_weights={'segmentation_output': 0.5, \"classification_output\": 0.5},\n",
    "              optimizer=opt, \n",
    "              metrics={'segmentation_output':['accuracy', dice_coef], 'classification_output':'accuracy'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "49cf0bf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================================ begin training ================================================\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow/python/ops/math_grad.py:102: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Deprecated in favor of operator or tf.math.divide.\n",
      "Train on 1000 samples, validate on 64 samples\n",
      "Epoch 1/200\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-21 01:16:29.440701: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.6351 - classification_output_loss: 0.9326 - segmentation_output_loss: 0.3377 - classification_output_acc: 0.5820 - segmentation_output_acc: 0.8762 - segmentation_output_dice_coef: 0.7966 - val_loss: 0.4309 - val_classification_output_loss: 0.6168 - val_segmentation_output_loss: 0.2451 - val_classification_output_acc: 0.7031 - val_segmentation_output_acc: 0.9149 - val_segmentation_output_dice_coef: 0.8340\n",
      "Epoch 2/200\n",
      "1000/1000 [==============================] - 29s 29ms/step - loss: 0.4770 - classification_output_loss: 0.6680 - segmentation_output_loss: 0.2860 - classification_output_acc: 0.5710 - segmentation_output_acc: 0.8863 - segmentation_output_dice_coef: 0.8247 - val_loss: 0.4397 - val_classification_output_loss: 0.6675 - val_segmentation_output_loss: 0.2118 - val_classification_output_acc: 0.5156 - val_segmentation_output_acc: 0.9178 - val_segmentation_output_dice_coef: 0.8706\n",
      "Epoch 3/200\n",
      "1000/1000 [==============================] - 30s 30ms/step - loss: 0.4525 - classification_output_loss: 0.6456 - segmentation_output_loss: 0.2594 - classification_output_acc: 0.6320 - segmentation_output_acc: 0.8956 - segmentation_output_dice_coef: 0.8437 - val_loss: 0.4089 - val_classification_output_loss: 0.6180 - val_segmentation_output_loss: 0.1997 - val_classification_output_acc: 0.6875 - val_segmentation_output_acc: 0.9241 - val_segmentation_output_dice_coef: 0.8930\n",
      "Epoch 4/200\n",
      "1000/1000 [==============================] - 38s 38ms/step - loss: 0.4422 - classification_output_loss: 0.6421 - segmentation_output_loss: 0.2423 - classification_output_acc: 0.6350 - segmentation_output_acc: 0.9047 - segmentation_output_dice_coef: 0.8539 - val_loss: 0.3923 - val_classification_output_loss: 0.5529 - val_segmentation_output_loss: 0.2317 - val_classification_output_acc: 0.7812 - val_segmentation_output_acc: 0.9118 - val_segmentation_output_dice_coef: 0.8455\n",
      "Epoch 5/200\n",
      "1000/1000 [==============================] - 46s 46ms/step - loss: 0.4183 - classification_output_loss: 0.6076 - segmentation_output_loss: 0.2291 - classification_output_acc: 0.6660 - segmentation_output_acc: 0.9094 - segmentation_output_dice_coef: 0.8632 - val_loss: 0.4033 - val_classification_output_loss: 0.6272 - val_segmentation_output_loss: 0.1793 - val_classification_output_acc: 0.6250 - val_segmentation_output_acc: 0.9311 - val_segmentation_output_dice_coef: 0.8949\n",
      "Epoch 6/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.3959 - classification_output_loss: 0.5735 - segmentation_output_loss: 0.2184 - classification_output_acc: 0.7000 - segmentation_output_acc: 0.9142 - segmentation_output_dice_coef: 0.8686 - val_loss: 0.3835 - val_classification_output_loss: 0.5726 - val_segmentation_output_loss: 0.1944 - val_classification_output_acc: 0.7031 - val_segmentation_output_acc: 0.9267 - val_segmentation_output_dice_coef: 0.8749\n",
      "Epoch 7/200\n",
      "1000/1000 [==============================] - 51s 51ms/step - loss: 0.3718 - classification_output_loss: 0.5433 - segmentation_output_loss: 0.2003 - classification_output_acc: 0.7400 - segmentation_output_acc: 0.9226 - segmentation_output_dice_coef: 0.8815 - val_loss: 0.3309 - val_classification_output_loss: 0.4816 - val_segmentation_output_loss: 0.1802 - val_classification_output_acc: 0.8125 - val_segmentation_output_acc: 0.9321 - val_segmentation_output_dice_coef: 0.9070\n",
      "Epoch 8/200\n",
      "1000/1000 [==============================] - 51s 51ms/step - loss: 0.3492 - classification_output_loss: 0.5111 - segmentation_output_loss: 0.1873 - classification_output_acc: 0.7700 - segmentation_output_acc: 0.9271 - segmentation_output_dice_coef: 0.8884 - val_loss: 0.3705 - val_classification_output_loss: 0.5635 - val_segmentation_output_loss: 0.1776 - val_classification_output_acc: 0.7188 - val_segmentation_output_acc: 0.9331 - val_segmentation_output_dice_coef: 0.8972\n",
      "Epoch 9/200\n",
      "1000/1000 [==============================] - 51s 51ms/step - loss: 0.3282 - classification_output_loss: 0.4766 - segmentation_output_loss: 0.1798 - classification_output_acc: 0.8030 - segmentation_output_acc: 0.9308 - segmentation_output_dice_coef: 0.8945 - val_loss: 0.2746 - val_classification_output_loss: 0.3832 - val_segmentation_output_loss: 0.1660 - val_classification_output_acc: 0.8906 - val_segmentation_output_acc: 0.9394 - val_segmentation_output_dice_coef: 0.9145\n",
      "Epoch 10/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.3089 - classification_output_loss: 0.4491 - segmentation_output_loss: 0.1687 - classification_output_acc: 0.8330 - segmentation_output_acc: 0.9346 - segmentation_output_dice_coef: 0.8993 - val_loss: 0.3092 - val_classification_output_loss: 0.4396 - val_segmentation_output_loss: 0.1788 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9388 - val_segmentation_output_dice_coef: 0.9089\n",
      "Epoch 11/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2815 - classification_output_loss: 0.4010 - segmentation_output_loss: 0.1620 - classification_output_acc: 0.8680 - segmentation_output_acc: 0.9378 - segmentation_output_dice_coef: 0.9041 - val_loss: 0.3345 - val_classification_output_loss: 0.4376 - val_segmentation_output_loss: 0.2314 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9252 - val_segmentation_output_dice_coef: 0.9142\n",
      "Epoch 12/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2651 - classification_output_loss: 0.3748 - segmentation_output_loss: 0.1553 - classification_output_acc: 0.8850 - segmentation_output_acc: 0.9396 - segmentation_output_dice_coef: 0.9072 - val_loss: 0.3357 - val_classification_output_loss: 0.4818 - val_segmentation_output_loss: 0.1896 - val_classification_output_acc: 0.7812 - val_segmentation_output_acc: 0.9285 - val_segmentation_output_dice_coef: 0.8935\n",
      "Epoch 13/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2469 - classification_output_loss: 0.3493 - segmentation_output_loss: 0.1444 - classification_output_acc: 0.9040 - segmentation_output_acc: 0.9446 - segmentation_output_dice_coef: 0.9141 - val_loss: 0.2741 - val_classification_output_loss: 0.3842 - val_segmentation_output_loss: 0.1640 - val_classification_output_acc: 0.8750 - val_segmentation_output_acc: 0.9440 - val_segmentation_output_dice_coef: 0.9180\n",
      "Epoch 14/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2364 - classification_output_loss: 0.3360 - segmentation_output_loss: 0.1368 - classification_output_acc: 0.9230 - segmentation_output_acc: 0.9465 - segmentation_output_dice_coef: 0.9185 - val_loss: 0.2951 - val_classification_output_loss: 0.3884 - val_segmentation_output_loss: 0.2019 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9258 - val_segmentation_output_dice_coef: 0.8839\n",
      "Epoch 15/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2236 - classification_output_loss: 0.3171 - segmentation_output_loss: 0.1302 - classification_output_acc: 0.9330 - segmentation_output_acc: 0.9503 - segmentation_output_dice_coef: 0.9230 - val_loss: 0.2398 - val_classification_output_loss: 0.2965 - val_segmentation_output_loss: 0.1832 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9398 - val_segmentation_output_dice_coef: 0.9279\n",
      "Epoch 16/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1996 - classification_output_loss: 0.2821 - segmentation_output_loss: 0.1172 - classification_output_acc: 0.9520 - segmentation_output_acc: 0.9554 - segmentation_output_dice_coef: 0.9303 - val_loss: 0.3663 - val_classification_output_loss: 0.4752 - val_segmentation_output_loss: 0.2574 - val_classification_output_acc: 0.8906 - val_segmentation_output_acc: 0.9247 - val_segmentation_output_dice_coef: 0.9223\n",
      "Epoch 17/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.2026 - classification_output_loss: 0.2898 - segmentation_output_loss: 0.1154 - classification_output_acc: 0.9320 - segmentation_output_acc: 0.9557 - segmentation_output_dice_coef: 0.9314 - val_loss: 0.3593 - val_classification_output_loss: 0.5092 - val_segmentation_output_loss: 0.2095 - val_classification_output_acc: 0.7812 - val_segmentation_output_acc: 0.9266 - val_segmentation_output_dice_coef: 0.8955\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 18/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1918 - classification_output_loss: 0.2773 - segmentation_output_loss: 0.1064 - classification_output_acc: 0.9470 - segmentation_output_acc: 0.9593 - segmentation_output_dice_coef: 0.9360 - val_loss: 0.2317 - val_classification_output_loss: 0.2772 - val_segmentation_output_loss: 0.1862 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9462 - val_segmentation_output_dice_coef: 0.9296\n",
      "Epoch 19/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1884 - classification_output_loss: 0.2770 - segmentation_output_loss: 0.0999 - classification_output_acc: 0.9430 - segmentation_output_acc: 0.9615 - segmentation_output_dice_coef: 0.9399 - val_loss: 0.2249 - val_classification_output_loss: 0.2523 - val_segmentation_output_loss: 0.1975 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9430 - val_segmentation_output_dice_coef: 0.9342\n",
      "Epoch 20/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1746 - classification_output_loss: 0.2565 - segmentation_output_loss: 0.0928 - classification_output_acc: 0.9590 - segmentation_output_acc: 0.9636 - segmentation_output_dice_coef: 0.9444 - val_loss: 0.2143 - val_classification_output_loss: 0.2190 - val_segmentation_output_loss: 0.2096 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9365 - val_segmentation_output_dice_coef: 0.9141\n",
      "Epoch 21/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1588 - classification_output_loss: 0.2294 - segmentation_output_loss: 0.0881 - classification_output_acc: 0.9770 - segmentation_output_acc: 0.9655 - segmentation_output_dice_coef: 0.9465 - val_loss: 0.3827 - val_classification_output_loss: 0.5778 - val_segmentation_output_loss: 0.1876 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9471 - val_segmentation_output_dice_coef: 0.9356\n",
      "Epoch 22/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1584 - classification_output_loss: 0.2341 - segmentation_output_loss: 0.0827 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9678 - segmentation_output_dice_coef: 0.9496 - val_loss: 0.3024 - val_classification_output_loss: 0.3867 - val_segmentation_output_loss: 0.2181 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9429 - val_segmentation_output_dice_coef: 0.9342\n",
      "Epoch 23/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1537 - classification_output_loss: 0.2302 - segmentation_output_loss: 0.0772 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9699 - segmentation_output_dice_coef: 0.9527 - val_loss: 0.2081 - val_classification_output_loss: 0.2197 - val_segmentation_output_loss: 0.1966 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9456 - val_segmentation_output_dice_coef: 0.9307\n",
      "Epoch 24/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1557 - classification_output_loss: 0.2378 - segmentation_output_loss: 0.0735 - classification_output_acc: 0.9540 - segmentation_output_acc: 0.9710 - segmentation_output_dice_coef: 0.9550 - val_loss: 0.2122 - val_classification_output_loss: 0.2363 - val_segmentation_output_loss: 0.1882 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9487 - val_segmentation_output_dice_coef: 0.9335\n",
      "Epoch 25/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1342 - classification_output_loss: 0.2013 - segmentation_output_loss: 0.0671 - classification_output_acc: 0.9760 - segmentation_output_acc: 0.9738 - segmentation_output_dice_coef: 0.9585 - val_loss: 0.6866 - val_classification_output_loss: 1.1532 - val_segmentation_output_loss: 0.2201 - val_classification_output_acc: 0.8594 - val_segmentation_output_acc: 0.9411 - val_segmentation_output_dice_coef: 0.9327\n",
      "Epoch 26/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1498 - classification_output_loss: 0.2312 - segmentation_output_loss: 0.0685 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9725 - segmentation_output_dice_coef: 0.9581 - val_loss: 0.2088 - val_classification_output_loss: 0.2181 - val_segmentation_output_loss: 0.1996 - val_classification_output_acc: 0.9688 - val_segmentation_output_acc: 0.9478 - val_segmentation_output_dice_coef: 0.9387\n",
      "Epoch 27/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1362 - classification_output_loss: 0.2141 - segmentation_output_loss: 0.0584 - classification_output_acc: 0.9580 - segmentation_output_acc: 0.9767 - segmentation_output_dice_coef: 0.9632 - val_loss: 0.2425 - val_classification_output_loss: 0.2860 - val_segmentation_output_loss: 0.1989 - val_classification_output_acc: 0.8906 - val_segmentation_output_acc: 0.9494 - val_segmentation_output_dice_coef: 0.9397\n",
      "Epoch 28/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1370 - classification_output_loss: 0.2171 - segmentation_output_loss: 0.0569 - classification_output_acc: 0.9590 - segmentation_output_acc: 0.9773 - segmentation_output_dice_coef: 0.9650 - val_loss: 0.2385 - val_classification_output_loss: 0.2607 - val_segmentation_output_loss: 0.2164 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9463 - val_segmentation_output_dice_coef: 0.9397\n",
      "Epoch 29/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1368 - classification_output_loss: 0.2188 - segmentation_output_loss: 0.0549 - classification_output_acc: 0.9550 - segmentation_output_acc: 0.9779 - segmentation_output_dice_coef: 0.9659 - val_loss: 0.2999 - val_classification_output_loss: 0.3941 - val_segmentation_output_loss: 0.2057 - val_classification_output_acc: 0.8594 - val_segmentation_output_acc: 0.9436 - val_segmentation_output_dice_coef: 0.9319\n",
      "Epoch 30/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1308 - classification_output_loss: 0.2113 - segmentation_output_loss: 0.0502 - classification_output_acc: 0.9610 - segmentation_output_acc: 0.9797 - segmentation_output_dice_coef: 0.9685 - val_loss: 0.3545 - val_classification_output_loss: 0.4646 - val_segmentation_output_loss: 0.2444 - val_classification_output_acc: 0.8125 - val_segmentation_output_acc: 0.9442 - val_segmentation_output_dice_coef: 0.9370\n",
      "Epoch 31/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1252 - classification_output_loss: 0.2024 - segmentation_output_loss: 0.0479 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9806 - segmentation_output_dice_coef: 0.9700 - val_loss: 0.2217 - val_classification_output_loss: 0.2407 - val_segmentation_output_loss: 0.2027 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9491 - val_segmentation_output_dice_coef: 0.9388\n",
      "Epoch 32/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1275 - classification_output_loss: 0.2066 - segmentation_output_loss: 0.0484 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9803 - segmentation_output_dice_coef: 0.9701 - val_loss: 0.3048 - val_classification_output_loss: 0.4035 - val_segmentation_output_loss: 0.2061 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9479 - val_segmentation_output_dice_coef: 0.9401\n",
      "Epoch 33/200\n",
      "1000/1000 [==============================] - 52s 52ms/step - loss: 0.1251 - classification_output_loss: 0.2072 - segmentation_output_loss: 0.0430 - classification_output_acc: 0.9530 - segmentation_output_acc: 0.9824 - segmentation_output_dice_coef: 0.9724 - val_loss: 0.4108 - val_classification_output_loss: 0.5819 - val_segmentation_output_loss: 0.2396 - val_classification_output_acc: 0.8281 - val_segmentation_output_acc: 0.9466 - val_segmentation_output_dice_coef: 0.9406\n",
      "Epoch 34/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1267 - classification_output_loss: 0.2074 - segmentation_output_loss: 0.0459 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9812 - segmentation_output_dice_coef: 0.9717 - val_loss: 0.4314 - val_classification_output_loss: 0.6347 - val_segmentation_output_loss: 0.2281 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9446 - val_segmentation_output_dice_coef: 0.9383\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 35/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1255 - classification_output_loss: 0.2109 - segmentation_output_loss: 0.0402 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9834 - segmentation_output_dice_coef: 0.9744 - val_loss: 0.2329 - val_classification_output_loss: 0.2443 - val_segmentation_output_loss: 0.2215 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9467 - val_segmentation_output_dice_coef: 0.9396\n",
      "Epoch 36/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1183 - classification_output_loss: 0.1984 - segmentation_output_loss: 0.0383 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9840 - segmentation_output_dice_coef: 0.9756 - val_loss: 0.2531 - val_classification_output_loss: 0.2732 - val_segmentation_output_loss: 0.2330 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9414 - val_segmentation_output_dice_coef: 0.9319\n",
      "Epoch 37/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1221 - classification_output_loss: 0.2048 - segmentation_output_loss: 0.0395 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9836 - segmentation_output_dice_coef: 0.9750 - val_loss: 0.2263 - val_classification_output_loss: 0.2063 - val_segmentation_output_loss: 0.2463 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9406 - val_segmentation_output_dice_coef: 0.9349\n",
      "Epoch 38/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1207 - classification_output_loss: 0.2050 - segmentation_output_loss: 0.0364 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9847 - segmentation_output_dice_coef: 0.9768 - val_loss: 0.5683 - val_classification_output_loss: 0.8986 - val_segmentation_output_loss: 0.2380 - val_classification_output_acc: 0.7500 - val_segmentation_output_acc: 0.9440 - val_segmentation_output_dice_coef: 0.9379\n",
      "Epoch 39/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1263 - classification_output_loss: 0.2141 - segmentation_output_loss: 0.0385 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9840 - segmentation_output_dice_coef: 0.9759 - val_loss: 0.2298 - val_classification_output_loss: 0.2273 - val_segmentation_output_loss: 0.2323 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9412 - val_segmentation_output_dice_coef: 0.9320\n",
      "Epoch 40/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1121 - classification_output_loss: 0.1882 - segmentation_output_loss: 0.0360 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9849 - segmentation_output_dice_coef: 0.9771 - val_loss: 0.4035 - val_classification_output_loss: 0.5951 - val_segmentation_output_loss: 0.2120 - val_classification_output_acc: 0.8594 - val_segmentation_output_acc: 0.9501 - val_segmentation_output_dice_coef: 0.9442\n",
      "Epoch 41/200\n",
      "1000/1000 [==============================] - 53s 53ms/step - loss: 0.1172 - classification_output_loss: 0.2012 - segmentation_output_loss: 0.0332 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9859 - segmentation_output_dice_coef: 0.9783 - val_loss: 0.2428 - val_classification_output_loss: 0.2545 - val_segmentation_output_loss: 0.2310 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9491 - val_segmentation_output_dice_coef: 0.9440\n",
      "Epoch 42/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1174 - classification_output_loss: 0.1985 - segmentation_output_loss: 0.0363 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9846 - segmentation_output_dice_coef: 0.9770 - val_loss: 0.2767 - val_classification_output_loss: 0.3307 - val_segmentation_output_loss: 0.2226 - val_classification_output_acc: 0.8906 - val_segmentation_output_acc: 0.9501 - val_segmentation_output_dice_coef: 0.9440\n",
      "Epoch 43/200\n",
      "1000/1000 [==============================] - 54s 54ms/step - loss: 0.1155 - classification_output_loss: 0.2015 - segmentation_output_loss: 0.0295 - classification_output_acc: 0.9780 - segmentation_output_acc: 0.9873 - segmentation_output_dice_coef: 0.9803 - val_loss: 0.2616 - val_classification_output_loss: 0.2957 - val_segmentation_output_loss: 0.2275 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9487 - val_segmentation_output_dice_coef: 0.9429\n",
      "Epoch 44/200\n",
      "1000/1000 [==============================] - 55s 55ms/step - loss: 0.1209 - classification_output_loss: 0.2130 - segmentation_output_loss: 0.0287 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9876 - segmentation_output_dice_coef: 0.9808 - val_loss: 0.3541 - val_classification_output_loss: 0.4644 - val_segmentation_output_loss: 0.2438 - val_classification_output_acc: 0.8281 - val_segmentation_output_acc: 0.9485 - val_segmentation_output_dice_coef: 0.9433\n",
      "Epoch 45/200\n",
      "1000/1000 [==============================] - 51s 51ms/step - loss: 0.1147 - classification_output_loss: 0.2005 - segmentation_output_loss: 0.0290 - classification_output_acc: 0.9630 - segmentation_output_acc: 0.9874 - segmentation_output_dice_coef: 0.9811 - val_loss: 0.2380 - val_classification_output_loss: 0.2343 - val_segmentation_output_loss: 0.2416 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9477 - val_segmentation_output_dice_coef: 0.9432\n",
      "Epoch 46/200\n",
      "1000/1000 [==============================] - 51s 51ms/step - loss: 0.1204 - classification_output_loss: 0.2117 - segmentation_output_loss: 0.0291 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9874 - segmentation_output_dice_coef: 0.9812 - val_loss: 0.3893 - val_classification_output_loss: 0.5393 - val_segmentation_output_loss: 0.2394 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9432 - val_segmentation_output_dice_coef: 0.9366\n",
      "Epoch 47/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1188 - classification_output_loss: 0.2083 - segmentation_output_loss: 0.0294 - classification_output_acc: 0.9600 - segmentation_output_acc: 0.9872 - segmentation_output_dice_coef: 0.9809 - val_loss: 0.2681 - val_classification_output_loss: 0.3203 - val_segmentation_output_loss: 0.2158 - val_classification_output_acc: 0.8906 - val_segmentation_output_acc: 0.9503 - val_segmentation_output_dice_coef: 0.9433\n",
      "Epoch 48/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1122 - classification_output_loss: 0.1987 - segmentation_output_loss: 0.0258 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9886 - segmentation_output_dice_coef: 0.9827 - val_loss: 0.2347 - val_classification_output_loss: 0.2391 - val_segmentation_output_loss: 0.2303 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9484 - val_segmentation_output_dice_coef: 0.9431\n",
      "Epoch 49/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1137 - classification_output_loss: 0.2022 - segmentation_output_loss: 0.0252 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9888 - segmentation_output_dice_coef: 0.9832 - val_loss: 0.2340 - val_classification_output_loss: 0.2429 - val_segmentation_output_loss: 0.2252 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9524 - val_segmentation_output_dice_coef: 0.9475\n",
      "Epoch 50/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1135 - classification_output_loss: 0.2010 - segmentation_output_loss: 0.0259 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9886 - segmentation_output_dice_coef: 0.9829 - val_loss: 0.3142 - val_classification_output_loss: 0.3920 - val_segmentation_output_loss: 0.2365 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9475 - val_segmentation_output_dice_coef: 0.9420\n",
      "Epoch 51/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1095 - classification_output_loss: 0.1951 - segmentation_output_loss: 0.0239 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9894 - segmentation_output_dice_coef: 0.9840 - val_loss: 0.3096 - val_classification_output_loss: 0.3540 - val_segmentation_output_loss: 0.2652 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9483 - val_segmentation_output_dice_coef: 0.9444\n"
     ]
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     "text": [
      "Epoch 52/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1084 - classification_output_loss: 0.1930 - segmentation_output_loss: 0.0238 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9894 - segmentation_output_dice_coef: 0.9841 - val_loss: 0.3261 - val_classification_output_loss: 0.4117 - val_segmentation_output_loss: 0.2406 - val_classification_output_acc: 0.8750 - val_segmentation_output_acc: 0.9497 - val_segmentation_output_dice_coef: 0.9451\n",
      "Epoch 53/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1067 - classification_output_loss: 0.1905 - segmentation_output_loss: 0.0229 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9897 - segmentation_output_dice_coef: 0.9846 - val_loss: 0.2830 - val_classification_output_loss: 0.3280 - val_segmentation_output_loss: 0.2381 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9493 - val_segmentation_output_dice_coef: 0.9445\n",
      "Epoch 54/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1140 - classification_output_loss: 0.2054 - segmentation_output_loss: 0.0227 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9897 - segmentation_output_dice_coef: 0.9847 - val_loss: 0.2977 - val_classification_output_loss: 0.3415 - val_segmentation_output_loss: 0.2539 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9483 - val_segmentation_output_dice_coef: 0.9441\n",
      "Epoch 55/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1016 - classification_output_loss: 0.1819 - segmentation_output_loss: 0.0214 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9902 - segmentation_output_dice_coef: 0.9855 - val_loss: 0.2903 - val_classification_output_loss: 0.3500 - val_segmentation_output_loss: 0.2306 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9502 - val_segmentation_output_dice_coef: 0.9446\n",
      "Epoch 56/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1031 - classification_output_loss: 0.1833 - segmentation_output_loss: 0.0230 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9896 - segmentation_output_dice_coef: 0.9849 - val_loss: 0.2692 - val_classification_output_loss: 0.2936 - val_segmentation_output_loss: 0.2448 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9505 - val_segmentation_output_dice_coef: 0.9464\n",
      "Epoch 57/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1036 - classification_output_loss: 0.1865 - segmentation_output_loss: 0.0207 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9905 - segmentation_output_dice_coef: 0.9859 - val_loss: 0.3141 - val_classification_output_loss: 0.3704 - val_segmentation_output_loss: 0.2579 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9496 - val_segmentation_output_dice_coef: 0.9456\n",
      "Epoch 58/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1051 - classification_output_loss: 0.1896 - segmentation_output_loss: 0.0206 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9905 - segmentation_output_dice_coef: 0.9859 - val_loss: 0.2970 - val_classification_output_loss: 0.3326 - val_segmentation_output_loss: 0.2615 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9489 - val_segmentation_output_dice_coef: 0.9451\n",
      "Epoch 59/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0997 - classification_output_loss: 0.1783 - segmentation_output_loss: 0.0211 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9903 - segmentation_output_dice_coef: 0.9858 - val_loss: 0.9242 - val_classification_output_loss: 1.5853 - val_segmentation_output_loss: 0.2631 - val_classification_output_acc: 0.8438 - val_segmentation_output_acc: 0.9470 - val_segmentation_output_dice_coef: 0.9428\n",
      "Epoch 60/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1081 - classification_output_loss: 0.1965 - segmentation_output_loss: 0.0198 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9908 - segmentation_output_dice_coef: 0.9864 - val_loss: 0.4300 - val_classification_output_loss: 0.6069 - val_segmentation_output_loss: 0.2530 - val_classification_output_acc: 0.8281 - val_segmentation_output_acc: 0.9454 - val_segmentation_output_dice_coef: 0.9407\n",
      "Epoch 61/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1056 - classification_output_loss: 0.1931 - segmentation_output_loss: 0.0181 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9915 - segmentation_output_dice_coef: 0.9873 - val_loss: 0.2979 - val_classification_output_loss: 0.3436 - val_segmentation_output_loss: 0.2521 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9485 - val_segmentation_output_dice_coef: 0.9443\n",
      "Epoch 62/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1052 - classification_output_loss: 0.1900 - segmentation_output_loss: 0.0203 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9906 - segmentation_output_dice_coef: 0.9864 - val_loss: 0.2618 - val_classification_output_loss: 0.2589 - val_segmentation_output_loss: 0.2646 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9478 - val_segmentation_output_dice_coef: 0.9442\n",
      "Epoch 63/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1048 - classification_output_loss: 0.1917 - segmentation_output_loss: 0.0179 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9915 - segmentation_output_dice_coef: 0.9874 - val_loss: 0.2680 - val_classification_output_loss: 0.2745 - val_segmentation_output_loss: 0.2614 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9498 - val_segmentation_output_dice_coef: 0.9463\n",
      "Epoch 64/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1119 - classification_output_loss: 0.2054 - segmentation_output_loss: 0.0185 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9913 - segmentation_output_dice_coef: 0.9874 - val_loss: 0.3751 - val_classification_output_loss: 0.4927 - val_segmentation_output_loss: 0.2574 - val_classification_output_acc: 0.8750 - val_segmentation_output_acc: 0.9437 - val_segmentation_output_dice_coef: 0.9388\n",
      "Epoch 65/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1094 - classification_output_loss: 0.2006 - segmentation_output_loss: 0.0182 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9914 - segmentation_output_dice_coef: 0.9875 - val_loss: 0.3014 - val_classification_output_loss: 0.3399 - val_segmentation_output_loss: 0.2629 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9509 - val_segmentation_output_dice_coef: 0.9474\n",
      "Epoch 66/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1042 - classification_output_loss: 0.1919 - segmentation_output_loss: 0.0165 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9921 - segmentation_output_dice_coef: 0.9883 - val_loss: 0.4186 - val_classification_output_loss: 0.5765 - val_segmentation_output_loss: 0.2607 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9492 - val_segmentation_output_dice_coef: 0.9452\n",
      "Epoch 67/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1087 - classification_output_loss: 0.2005 - segmentation_output_loss: 0.0168 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9919 - segmentation_output_dice_coef: 0.9882 - val_loss: 0.2719 - val_classification_output_loss: 0.2903 - val_segmentation_output_loss: 0.2535 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9505 - val_segmentation_output_dice_coef: 0.9468\n",
      "Epoch 68/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1116 - classification_output_loss: 0.2065 - segmentation_output_loss: 0.0166 - classification_output_acc: 0.9630 - segmentation_output_acc: 0.9919 - segmentation_output_dice_coef: 0.9882 - val_loss: 0.2861 - val_classification_output_loss: 0.3079 - val_segmentation_output_loss: 0.2643 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9500 - val_segmentation_output_dice_coef: 0.9467\n"
     ]
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     "text": [
      "Epoch 69/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0979 - classification_output_loss: 0.1792 - segmentation_output_loss: 0.0166 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9919 - segmentation_output_dice_coef: 0.9883 - val_loss: 0.2699 - val_classification_output_loss: 0.2722 - val_segmentation_output_loss: 0.2677 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9505 - val_segmentation_output_dice_coef: 0.9471\n",
      "Epoch 70/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1042 - classification_output_loss: 0.1924 - segmentation_output_loss: 0.0160 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9923 - segmentation_output_dice_coef: 0.9886 - val_loss: 0.2740 - val_classification_output_loss: 0.2850 - val_segmentation_output_loss: 0.2630 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9484 - val_segmentation_output_dice_coef: 0.9444\n",
      "Epoch 71/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1028 - classification_output_loss: 0.1901 - segmentation_output_loss: 0.0155 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9924 - segmentation_output_dice_coef: 0.9889 - val_loss: 0.2391 - val_classification_output_loss: 0.2145 - val_segmentation_output_loss: 0.2637 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9510 - val_segmentation_output_dice_coef: 0.9478\n",
      "Epoch 72/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0982 - classification_output_loss: 0.1807 - segmentation_output_loss: 0.0156 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9924 - segmentation_output_dice_coef: 0.9890 - val_loss: 0.2569 - val_classification_output_loss: 0.2212 - val_segmentation_output_loss: 0.2926 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9478 - val_segmentation_output_dice_coef: 0.9449\n",
      "Epoch 73/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0956 - classification_output_loss: 0.1752 - segmentation_output_loss: 0.0159 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9923 - segmentation_output_dice_coef: 0.9889 - val_loss: 0.2570 - val_classification_output_loss: 0.2495 - val_segmentation_output_loss: 0.2645 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9508 - val_segmentation_output_dice_coef: 0.9474\n",
      "Epoch 74/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1013 - classification_output_loss: 0.1877 - segmentation_output_loss: 0.0150 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9927 - segmentation_output_dice_coef: 0.9893 - val_loss: 0.2633 - val_classification_output_loss: 0.2589 - val_segmentation_output_loss: 0.2677 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9508 - val_segmentation_output_dice_coef: 0.9478\n",
      "Epoch 75/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1059 - classification_output_loss: 0.1963 - segmentation_output_loss: 0.0155 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9924 - segmentation_output_dice_coef: 0.9891 - val_loss: 0.2888 - val_classification_output_loss: 0.2886 - val_segmentation_output_loss: 0.2891 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9489 - val_segmentation_output_dice_coef: 0.9461\n",
      "Epoch 76/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1046 - classification_output_loss: 0.1941 - segmentation_output_loss: 0.0150 - classification_output_acc: 0.9630 - segmentation_output_acc: 0.9926 - segmentation_output_dice_coef: 0.9894 - val_loss: 0.2690 - val_classification_output_loss: 0.2625 - val_segmentation_output_loss: 0.2754 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9507 - val_segmentation_output_dice_coef: 0.9478\n",
      "Epoch 77/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1051 - classification_output_loss: 0.1956 - segmentation_output_loss: 0.0145 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9928 - segmentation_output_dice_coef: 0.9896 - val_loss: 0.2896 - val_classification_output_loss: 0.2885 - val_segmentation_output_loss: 0.2907 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9480 - val_segmentation_output_dice_coef: 0.9449\n",
      "Epoch 78/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1034 - classification_output_loss: 0.1910 - segmentation_output_loss: 0.0157 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9923 - segmentation_output_dice_coef: 0.9891 - val_loss: 0.2856 - val_classification_output_loss: 0.3098 - val_segmentation_output_loss: 0.2615 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9499 - val_segmentation_output_dice_coef: 0.9464\n",
      "Epoch 79/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1013 - classification_output_loss: 0.1884 - segmentation_output_loss: 0.0143 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9929 - segmentation_output_dice_coef: 0.9896 - val_loss: 0.2644 - val_classification_output_loss: 0.2543 - val_segmentation_output_loss: 0.2745 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9508 - val_segmentation_output_dice_coef: 0.9473\n",
      "Epoch 80/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0995 - classification_output_loss: 0.1851 - segmentation_output_loss: 0.0140 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9930 - segmentation_output_dice_coef: 0.9898 - val_loss: 0.3923 - val_classification_output_loss: 0.5161 - val_segmentation_output_loss: 0.2685 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9504 - val_segmentation_output_dice_coef: 0.9466\n",
      "Epoch 81/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1045 - classification_output_loss: 0.1961 - segmentation_output_loss: 0.0130 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9934 - segmentation_output_dice_coef: 0.9903 - val_loss: 0.2945 - val_classification_output_loss: 0.3176 - val_segmentation_output_loss: 0.2714 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9499 - val_segmentation_output_dice_coef: 0.9462\n",
      "Epoch 82/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0961 - classification_output_loss: 0.1787 - segmentation_output_loss: 0.0136 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9932 - segmentation_output_dice_coef: 0.9902 - val_loss: 0.2963 - val_classification_output_loss: 0.3022 - val_segmentation_output_loss: 0.2904 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9505 - val_segmentation_output_dice_coef: 0.9477\n",
      "Epoch 83/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0973 - classification_output_loss: 0.1807 - segmentation_output_loss: 0.0139 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9930 - segmentation_output_dice_coef: 0.9900 - val_loss: 0.2990 - val_classification_output_loss: 0.3123 - val_segmentation_output_loss: 0.2857 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9483\n",
      "Epoch 84/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0963 - classification_output_loss: 0.1796 - segmentation_output_loss: 0.0130 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9934 - segmentation_output_dice_coef: 0.9905 - val_loss: 0.2815 - val_classification_output_loss: 0.2785 - val_segmentation_output_loss: 0.2845 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9485\n",
      "Epoch 85/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0997 - classification_output_loss: 0.1867 - segmentation_output_loss: 0.0127 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9935 - segmentation_output_dice_coef: 0.9906 - val_loss: 0.2614 - val_classification_output_loss: 0.2316 - val_segmentation_output_loss: 0.2912 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9494 - val_segmentation_output_dice_coef: 0.9464\n"
     ]
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     "text": [
      "Epoch 86/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0996 - classification_output_loss: 0.1865 - segmentation_output_loss: 0.0126 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9935 - segmentation_output_dice_coef: 0.9907 - val_loss: 0.2643 - val_classification_output_loss: 0.2520 - val_segmentation_output_loss: 0.2765 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9498 - val_segmentation_output_dice_coef: 0.9464\n",
      "Epoch 87/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1086 - classification_output_loss: 0.2045 - segmentation_output_loss: 0.0127 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9935 - segmentation_output_dice_coef: 0.9907 - val_loss: 0.2619 - val_classification_output_loss: 0.2465 - val_segmentation_output_loss: 0.2774 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9485\n",
      "Epoch 88/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1002 - classification_output_loss: 0.1874 - segmentation_output_loss: 0.0129 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9934 - segmentation_output_dice_coef: 0.9906 - val_loss: 0.2745 - val_classification_output_loss: 0.2694 - val_segmentation_output_loss: 0.2796 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9513 - val_segmentation_output_dice_coef: 0.9484\n",
      "Epoch 89/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1020 - classification_output_loss: 0.1918 - segmentation_output_loss: 0.0123 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9936 - segmentation_output_dice_coef: 0.9909 - val_loss: 0.2736 - val_classification_output_loss: 0.2662 - val_segmentation_output_loss: 0.2809 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 90/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1006 - classification_output_loss: 0.1889 - segmentation_output_loss: 0.0122 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9937 - segmentation_output_dice_coef: 0.9910 - val_loss: 0.2827 - val_classification_output_loss: 0.2849 - val_segmentation_output_loss: 0.2805 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9483\n",
      "Epoch 91/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1005 - classification_output_loss: 0.1888 - segmentation_output_loss: 0.0123 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9937 - segmentation_output_dice_coef: 0.9910 - val_loss: 0.3728 - val_classification_output_loss: 0.4591 - val_segmentation_output_loss: 0.2864 - val_classification_output_acc: 0.9062 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 92/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1078 - classification_output_loss: 0.2041 - segmentation_output_loss: 0.0115 - classification_output_acc: 0.9630 - segmentation_output_acc: 0.9939 - segmentation_output_dice_coef: 0.9913 - val_loss: 0.2710 - val_classification_output_loss: 0.2664 - val_segmentation_output_loss: 0.2756 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9484 - val_segmentation_output_dice_coef: 0.9448\n",
      "Epoch 93/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1030 - classification_output_loss: 0.1943 - segmentation_output_loss: 0.0116 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9939 - segmentation_output_dice_coef: 0.9913 - val_loss: 0.2662 - val_classification_output_loss: 0.2565 - val_segmentation_output_loss: 0.2759 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9509 - val_segmentation_output_dice_coef: 0.9479\n",
      "\n",
      "Epoch 00093: ReduceLROnPlateau reducing learning rate to 9.000000427477062e-05.\n",
      "Epoch 94/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0959 - classification_output_loss: 0.1802 - segmentation_output_loss: 0.0116 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9940 - segmentation_output_dice_coef: 0.9914 - val_loss: 0.2673 - val_classification_output_loss: 0.2527 - val_segmentation_output_loss: 0.2820 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9509 - val_segmentation_output_dice_coef: 0.9478\n",
      "Epoch 95/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0988 - classification_output_loss: 0.1866 - segmentation_output_loss: 0.0109 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9942 - segmentation_output_dice_coef: 0.9916 - val_loss: 0.2893 - val_classification_output_loss: 0.2924 - val_segmentation_output_loss: 0.2862 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9486\n",
      "Epoch 96/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1007 - classification_output_loss: 0.1909 - segmentation_output_loss: 0.0106 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9944 - segmentation_output_dice_coef: 0.9918 - val_loss: 0.2731 - val_classification_output_loss: 0.2605 - val_segmentation_output_loss: 0.2856 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9484\n",
      "Epoch 97/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1007 - classification_output_loss: 0.1910 - segmentation_output_loss: 0.0105 - classification_output_acc: 0.9600 - segmentation_output_acc: 0.9944 - segmentation_output_dice_coef: 0.9918 - val_loss: 0.2962 - val_classification_output_loss: 0.3011 - val_segmentation_output_loss: 0.2913 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9484\n",
      "Epoch 98/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1007 - classification_output_loss: 0.1912 - segmentation_output_loss: 0.0101 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9945 - segmentation_output_dice_coef: 0.9920 - val_loss: 0.3278 - val_classification_output_loss: 0.3678 - val_segmentation_output_loss: 0.2878 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9520 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 99/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1033 - classification_output_loss: 0.1963 - segmentation_output_loss: 0.0102 - classification_output_acc: 0.9610 - segmentation_output_acc: 0.9945 - segmentation_output_dice_coef: 0.9920 - val_loss: 0.3031 - val_classification_output_loss: 0.3174 - val_segmentation_output_loss: 0.2889 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 100/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0982 - classification_output_loss: 0.1867 - segmentation_output_loss: 0.0098 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9922 - val_loss: 0.2898 - val_classification_output_loss: 0.2957 - val_segmentation_output_loss: 0.2840 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9482\n",
      "Epoch 101/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1068 - classification_output_loss: 0.2036 - segmentation_output_loss: 0.0100 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9921 - val_loss: 0.2893 - val_classification_output_loss: 0.2879 - val_segmentation_output_loss: 0.2906 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9510 - val_segmentation_output_dice_coef: 0.9482\n",
      "Epoch 102/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0943 - classification_output_loss: 0.1781 - segmentation_output_loss: 0.0104 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9944 - segmentation_output_dice_coef: 0.9920 - val_loss: 0.3041 - val_classification_output_loss: 0.3134 - val_segmentation_output_loss: 0.2947 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9511 - val_segmentation_output_dice_coef: 0.9484\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 103/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0985 - classification_output_loss: 0.1863 - segmentation_output_loss: 0.0107 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9943 - segmentation_output_dice_coef: 0.9919 - val_loss: 0.3020 - val_classification_output_loss: 0.3208 - val_segmentation_output_loss: 0.2833 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 104/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1016 - classification_output_loss: 0.1932 - segmentation_output_loss: 0.0099 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9922 - val_loss: 0.3042 - val_classification_output_loss: 0.3202 - val_segmentation_output_loss: 0.2882 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 105/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1022 - classification_output_loss: 0.1947 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.2926 - val_classification_output_loss: 0.2983 - val_segmentation_output_loss: 0.2868 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9513 - val_segmentation_output_dice_coef: 0.9484\n",
      "Epoch 106/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1047 - classification_output_loss: 0.1999 - segmentation_output_loss: 0.0095 - classification_output_acc: 0.9510 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9924 - val_loss: 0.2913 - val_classification_output_loss: 0.2893 - val_segmentation_output_loss: 0.2934 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9511 - val_segmentation_output_dice_coef: 0.9484\n",
      "Epoch 107/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0997 - classification_output_loss: 0.1898 - segmentation_output_loss: 0.0096 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9924 - val_loss: 0.2972 - val_classification_output_loss: 0.3008 - val_segmentation_output_loss: 0.2935 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9513 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 108/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1060 - classification_output_loss: 0.2023 - segmentation_output_loss: 0.0098 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.3773 - val_classification_output_loss: 0.4637 - val_segmentation_output_loss: 0.2910 - val_classification_output_acc: 0.9219 - val_segmentation_output_acc: 0.9520 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 109/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0960 - classification_output_loss: 0.1822 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.3507 - val_classification_output_loss: 0.4100 - val_segmentation_output_loss: 0.2913 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9519 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 110/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1002 - classification_output_loss: 0.1905 - segmentation_output_loss: 0.0099 - classification_output_acc: 0.9580 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.2953 - val_classification_output_loss: 0.3037 - val_segmentation_output_loss: 0.2869 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9519 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 111/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0998 - classification_output_loss: 0.1902 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2782 - val_classification_output_loss: 0.2663 - val_segmentation_output_loss: 0.2900 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 112/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0986 - classification_output_loss: 0.1872 - segmentation_output_loss: 0.0100 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9922 - val_loss: 0.2986 - val_classification_output_loss: 0.2984 - val_segmentation_output_loss: 0.2988 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9486\n",
      "Epoch 113/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1102 - classification_output_loss: 0.2076 - segmentation_output_loss: 0.0128 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9937 - segmentation_output_dice_coef: 0.9914 - val_loss: 0.2801 - val_classification_output_loss: 0.2669 - val_segmentation_output_loss: 0.2933 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9512 - val_segmentation_output_dice_coef: 0.9484\n",
      "\n",
      "Epoch 00113: ReduceLROnPlateau reducing learning rate to 2.700000040931627e-05.\n",
      "Epoch 114/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1062 - classification_output_loss: 0.2030 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2889 - val_classification_output_loss: 0.2855 - val_segmentation_output_loss: 0.2924 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 115/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0955 - classification_output_loss: 0.1815 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2921 - val_classification_output_loss: 0.2929 - val_segmentation_output_loss: 0.2912 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 116/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0982 - classification_output_loss: 0.1867 - segmentation_output_loss: 0.0096 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9924 - val_loss: 0.2890 - val_classification_output_loss: 0.2881 - val_segmentation_output_loss: 0.2899 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9486\n",
      "Epoch 117/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1111 - classification_output_loss: 0.2121 - segmentation_output_loss: 0.0100 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9946 - segmentation_output_dice_coef: 0.9922 - val_loss: 0.2833 - val_classification_output_loss: 0.2770 - val_segmentation_output_loss: 0.2897 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 118/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0961 - classification_output_loss: 0.1828 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2860 - val_classification_output_loss: 0.2837 - val_segmentation_output_loss: 0.2884 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 119/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0996 - classification_output_loss: 0.1895 - segmentation_output_loss: 0.0098 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9924 - val_loss: 0.2895 - val_classification_output_loss: 0.2892 - val_segmentation_output_loss: 0.2898 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 120/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1017 - classification_output_loss: 0.1938 - segmentation_output_loss: 0.0095 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2873 - val_classification_output_loss: 0.2852 - val_segmentation_output_loss: 0.2894 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 121/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1026 - classification_output_loss: 0.1955 - segmentation_output_loss: 0.0096 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9924 - val_loss: 0.2948 - val_classification_output_loss: 0.3001 - val_segmentation_output_loss: 0.2896 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 122/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0938 - classification_output_loss: 0.1778 - segmentation_output_loss: 0.0099 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.2885 - val_classification_output_loss: 0.2857 - val_segmentation_output_loss: 0.2914 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 123/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0961 - classification_output_loss: 0.1830 - segmentation_output_loss: 0.0093 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2945 - val_classification_output_loss: 0.2975 - val_segmentation_output_loss: 0.2914 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 124/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0945 - classification_output_loss: 0.1796 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2927 - val_classification_output_loss: 0.2925 - val_segmentation_output_loss: 0.2929 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 125/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1094 - classification_output_loss: 0.2095 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9600 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.2908 - val_classification_output_loss: 0.2888 - val_segmentation_output_loss: 0.2927 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 126/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1042 - classification_output_loss: 0.1987 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.3007 - val_classification_output_loss: 0.3088 - val_segmentation_output_loss: 0.2926 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 127/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0964 - classification_output_loss: 0.1830 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9923 - val_loss: 0.3017 - val_classification_output_loss: 0.3122 - val_segmentation_output_loss: 0.2911 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 128/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1047 - classification_output_loss: 0.1999 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9580 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2984 - val_classification_output_loss: 0.3042 - val_segmentation_output_loss: 0.2927 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 129/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0914 - classification_output_loss: 0.1734 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2955 - val_classification_output_loss: 0.2990 - val_segmentation_output_loss: 0.2920 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9486\n",
      "Epoch 130/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0953 - classification_output_loss: 0.1815 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.2911 - val_classification_output_loss: 0.2906 - val_segmentation_output_loss: 0.2917 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 131/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1017 - classification_output_loss: 0.1945 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3028 - val_classification_output_loss: 0.3124 - val_segmentation_output_loss: 0.2931 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 132/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0996 - classification_output_loss: 0.1902 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.2961 - val_classification_output_loss: 0.2983 - val_segmentation_output_loss: 0.2939 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 133/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0910 - classification_output_loss: 0.1727 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.3033 - val_classification_output_loss: 0.3137 - val_segmentation_output_loss: 0.2930 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 134/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0919 - classification_output_loss: 0.1744 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.2984 - val_classification_output_loss: 0.3055 - val_segmentation_output_loss: 0.2913 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 135/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1041 - classification_output_loss: 0.1988 - segmentation_output_loss: 0.0095 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.3069 - val_classification_output_loss: 0.3218 - val_segmentation_output_loss: 0.2920 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n"
     ]
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     "text": [
      "Epoch 136/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1002 - classification_output_loss: 0.1915 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9590 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.2943 - val_classification_output_loss: 0.2970 - val_segmentation_output_loss: 0.2916 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9487\n",
      "Epoch 137/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1021 - classification_output_loss: 0.1950 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.2974 - val_classification_output_loss: 0.3027 - val_segmentation_output_loss: 0.2921 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 138/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0968 - classification_output_loss: 0.1847 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3166 - val_classification_output_loss: 0.3410 - val_segmentation_output_loss: 0.2923 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 139/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0977 - classification_output_loss: 0.1860 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.3060 - val_classification_output_loss: 0.3192 - val_segmentation_output_loss: 0.2928 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 140/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1023 - classification_output_loss: 0.1956 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.2929 - val_classification_output_loss: 0.2926 - val_segmentation_output_loss: 0.2932 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 141/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0976 - classification_output_loss: 0.1863 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3054 - val_classification_output_loss: 0.3162 - val_segmentation_output_loss: 0.2947 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 142/200\n",
      "1000/1000 [==============================] - 50s 50ms/step - loss: 0.1117 - classification_output_loss: 0.2142 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9510 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3044 - val_classification_output_loss: 0.3138 - val_segmentation_output_loss: 0.2951 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 143/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0986 - classification_output_loss: 0.1885 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3042 - val_classification_output_loss: 0.3148 - val_segmentation_output_loss: 0.2936 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 144/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1029 - classification_output_loss: 0.1970 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9530 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3116 - val_classification_output_loss: 0.3273 - val_segmentation_output_loss: 0.2959 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 145/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0923 - classification_output_loss: 0.1753 - segmentation_output_loss: 0.0093 - classification_output_acc: 0.9720 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.2969 - val_classification_output_loss: 0.3003 - val_segmentation_output_loss: 0.2935 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 146/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0959 - classification_output_loss: 0.1827 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3023 - val_classification_output_loss: 0.3106 - val_segmentation_output_loss: 0.2940 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 147/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1038 - classification_output_loss: 0.1987 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3047 - val_classification_output_loss: 0.3139 - val_segmentation_output_loss: 0.2955 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 148/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0979 - classification_output_loss: 0.1868 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.2999 - val_classification_output_loss: 0.3079 - val_segmentation_output_loss: 0.2919 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 149/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0892 - classification_output_loss: 0.1697 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9760 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3020 - val_classification_output_loss: 0.3111 - val_segmentation_output_loss: 0.2928 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 150/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0956 - classification_output_loss: 0.1820 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.2981 - val_classification_output_loss: 0.3028 - val_segmentation_output_loss: 0.2933 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 151/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1014 - classification_output_loss: 0.1941 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.2995 - val_classification_output_loss: 0.3037 - val_segmentation_output_loss: 0.2953 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 152/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0926 - classification_output_loss: 0.1764 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3024 - val_classification_output_loss: 0.3100 - val_segmentation_output_loss: 0.2947 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9488\n"
     ]
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     "text": [
      "Epoch 153/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0951 - classification_output_loss: 0.1808 - segmentation_output_loss: 0.0095 - classification_output_acc: 0.9790 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.3019 - val_classification_output_loss: 0.3071 - val_segmentation_output_loss: 0.2966 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9515 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 154/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0948 - classification_output_loss: 0.1806 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9750 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.2970 - val_classification_output_loss: 0.2990 - val_segmentation_output_loss: 0.2950 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 155/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0922 - classification_output_loss: 0.1756 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.2965 - val_classification_output_loss: 0.2988 - val_segmentation_output_loss: 0.2942 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 156/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1013 - classification_output_loss: 0.1928 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9770 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.2982 - val_classification_output_loss: 0.3037 - val_segmentation_output_loss: 0.2928 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 157/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0969 - classification_output_loss: 0.1846 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3057 - val_classification_output_loss: 0.3166 - val_segmentation_output_loss: 0.2947 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 158/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0947 - classification_output_loss: 0.1802 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3046 - val_classification_output_loss: 0.3135 - val_segmentation_output_loss: 0.2957 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 159/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1048 - classification_output_loss: 0.2005 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9690 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3025 - val_classification_output_loss: 0.3114 - val_segmentation_output_loss: 0.2935 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 160/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1011 - classification_output_loss: 0.1933 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3026 - val_classification_output_loss: 0.3108 - val_segmentation_output_loss: 0.2943 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9489\n",
      "Epoch 161/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0912 - classification_output_loss: 0.1737 - segmentation_output_loss: 0.0086 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9930 - val_loss: 0.3158 - val_classification_output_loss: 0.3349 - val_segmentation_output_loss: 0.2967 - val_classification_output_acc: 0.9375 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 162/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1046 - classification_output_loss: 0.2002 - segmentation_output_loss: 0.0090 - classification_output_acc: 0.9630 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3044 - val_classification_output_loss: 0.3139 - val_segmentation_output_loss: 0.2948 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9493\n",
      "Epoch 163/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0992 - classification_output_loss: 0.1897 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3006 - val_classification_output_loss: 0.3044 - val_segmentation_output_loss: 0.2968 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9514 - val_segmentation_output_dice_coef: 0.9488\n",
      "Epoch 164/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0919 - classification_output_loss: 0.1748 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9790 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3014 - val_classification_output_loss: 0.3072 - val_segmentation_output_loss: 0.2955 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 165/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0905 - classification_output_loss: 0.1721 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.2971 - val_classification_output_loss: 0.3003 - val_segmentation_output_loss: 0.2939 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 166/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1018 - classification_output_loss: 0.1942 - segmentation_output_loss: 0.0093 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.3126 - val_classification_output_loss: 0.3302 - val_segmentation_output_loss: 0.2950 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9519 - val_segmentation_output_dice_coef: 0.9493\n",
      "Epoch 167/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0972 - classification_output_loss: 0.1854 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3039 - val_classification_output_loss: 0.3138 - val_segmentation_output_loss: 0.2940 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 168/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0961 - classification_output_loss: 0.1835 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9760 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3037 - val_classification_output_loss: 0.3137 - val_segmentation_output_loss: 0.2936 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 169/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0968 - classification_output_loss: 0.1845 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3084 - val_classification_output_loss: 0.3211 - val_segmentation_output_loss: 0.2956 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n"
     ]
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     "text": [
      "\n",
      "Epoch 00169: ReduceLROnPlateau reducing learning rate to 8.100000013655517e-06.\n",
      "Epoch 170/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0937 - classification_output_loss: 0.1785 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9650 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3051 - val_classification_output_loss: 0.3144 - val_segmentation_output_loss: 0.2958 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 171/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0969 - classification_output_loss: 0.1850 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9730 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3047 - val_classification_output_loss: 0.3131 - val_segmentation_output_loss: 0.2963 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 172/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1024 - classification_output_loss: 0.1960 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3027 - val_classification_output_loss: 0.3099 - val_segmentation_output_loss: 0.2955 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 173/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0961 - classification_output_loss: 0.1834 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3015 - val_classification_output_loss: 0.3079 - val_segmentation_output_loss: 0.2952 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 174/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0953 - classification_output_loss: 0.1816 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9610 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3015 - val_classification_output_loss: 0.3067 - val_segmentation_output_loss: 0.2963 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 175/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0994 - classification_output_loss: 0.1901 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3061 - val_classification_output_loss: 0.3170 - val_segmentation_output_loss: 0.2952 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 176/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0989 - classification_output_loss: 0.1890 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3051 - val_classification_output_loss: 0.3137 - val_segmentation_output_loss: 0.2964 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 177/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1059 - classification_output_loss: 0.2025 - segmentation_output_loss: 0.0093 - classification_output_acc: 0.9580 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3097 - val_classification_output_loss: 0.3217 - val_segmentation_output_loss: 0.2976 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9519 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 178/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0984 - classification_output_loss: 0.1877 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3079 - val_classification_output_loss: 0.3197 - val_segmentation_output_loss: 0.2960 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9519 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 179/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1016 - classification_output_loss: 0.1941 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3029 - val_classification_output_loss: 0.3101 - val_segmentation_output_loss: 0.2957 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 180/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0971 - classification_output_loss: 0.1853 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9790 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3040 - val_classification_output_loss: 0.3118 - val_segmentation_output_loss: 0.2962 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 181/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0964 - classification_output_loss: 0.1843 - segmentation_output_loss: 0.0086 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9930 - val_loss: 0.3056 - val_classification_output_loss: 0.3149 - val_segmentation_output_loss: 0.2962 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 182/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1042 - classification_output_loss: 0.1994 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9750 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3081 - val_classification_output_loss: 0.3196 - val_segmentation_output_loss: 0.2967 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 183/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0981 - classification_output_loss: 0.1870 - segmentation_output_loss: 0.0092 - classification_output_acc: 0.9620 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3094 - val_classification_output_loss: 0.3214 - val_segmentation_output_loss: 0.2975 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 184/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0926 - classification_output_loss: 0.1765 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3054 - val_classification_output_loss: 0.3150 - val_segmentation_output_loss: 0.2959 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 185/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1018 - classification_output_loss: 0.1950 - segmentation_output_loss: 0.0085 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9952 - segmentation_output_dice_coef: 0.9930 - val_loss: 0.3068 - val_classification_output_loss: 0.3165 - val_segmentation_output_loss: 0.2971 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 186/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1039 - classification_output_loss: 0.1986 - segmentation_output_loss: 0.0093 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3079 - val_classification_output_loss: 0.3191 - val_segmentation_output_loss: 0.2967 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9516 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 187/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0961 - classification_output_loss: 0.1834 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3044 - val_classification_output_loss: 0.3127 - val_segmentation_output_loss: 0.2961 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 188/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0963 - classification_output_loss: 0.1837 - segmentation_output_loss: 0.0088 - classification_output_acc: 0.9740 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3077 - val_classification_output_loss: 0.3195 - val_segmentation_output_loss: 0.2958 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9492\n",
      "Epoch 189/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.1054 - classification_output_loss: 0.2018 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9680 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3042 - val_classification_output_loss: 0.3114 - val_segmentation_output_loss: 0.2970 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "\n",
      "Epoch 00189: ReduceLROnPlateau reducing learning rate to 2.429999949526973e-06.\n",
      "Epoch 190/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.0996 - classification_output_loss: 0.1904 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3032 - val_classification_output_loss: 0.3100 - val_segmentation_output_loss: 0.2965 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 191/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0967 - classification_output_loss: 0.1836 - segmentation_output_loss: 0.0097 - classification_output_acc: 0.9750 - segmentation_output_acc: 0.9948 - segmentation_output_dice_coef: 0.9926 - val_loss: 0.3036 - val_classification_output_loss: 0.3104 - val_segmentation_output_loss: 0.2968 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 192/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0986 - classification_output_loss: 0.1882 - segmentation_output_loss: 0.0091 - classification_output_acc: 0.9700 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3041 - val_classification_output_loss: 0.3124 - val_segmentation_output_loss: 0.2958 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 193/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0996 - classification_output_loss: 0.1903 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3056 - val_classification_output_loss: 0.3147 - val_segmentation_output_loss: 0.2965 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 194/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0951 - classification_output_loss: 0.1803 - segmentation_output_loss: 0.0100 - classification_output_acc: 0.9710 - segmentation_output_acc: 0.9947 - segmentation_output_dice_coef: 0.9925 - val_loss: 0.3021 - val_classification_output_loss: 0.3079 - val_segmentation_output_loss: 0.2962 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "Epoch 195/200\n",
      "1000/1000 [==============================] - 49s 49ms/step - loss: 0.1079 - classification_output_loss: 0.2065 - segmentation_output_loss: 0.0094 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9949 - segmentation_output_dice_coef: 0.9927 - val_loss: 0.3035 - val_classification_output_loss: 0.3113 - val_segmentation_output_loss: 0.2957 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 196/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0994 - classification_output_loss: 0.1903 - segmentation_output_loss: 0.0086 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9930 - val_loss: 0.3009 - val_classification_output_loss: 0.3057 - val_segmentation_output_loss: 0.2961 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 197/200\n",
      "1000/1000 [==============================] - 47s 47ms/step - loss: 0.0945 - classification_output_loss: 0.1802 - segmentation_output_loss: 0.0087 - classification_output_acc: 0.9660 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3033 - val_classification_output_loss: 0.3105 - val_segmentation_output_loss: 0.2962 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9518 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 198/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1000 - classification_output_loss: 0.1913 - segmentation_output_loss: 0.0086 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9951 - segmentation_output_dice_coef: 0.9929 - val_loss: 0.3042 - val_classification_output_loss: 0.3124 - val_segmentation_output_loss: 0.2961 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 199/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.1026 - classification_output_loss: 0.1962 - segmentation_output_loss: 0.0089 - classification_output_acc: 0.9670 - segmentation_output_acc: 0.9950 - segmentation_output_dice_coef: 0.9928 - val_loss: 0.3030 - val_classification_output_loss: 0.3100 - val_segmentation_output_loss: 0.2960 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9491\n",
      "Epoch 200/200\n",
      "1000/1000 [==============================] - 48s 48ms/step - loss: 0.0991 - classification_output_loss: 0.1897 - segmentation_output_loss: 0.0085 - classification_output_acc: 0.9640 - segmentation_output_acc: 0.9952 - segmentation_output_dice_coef: 0.9930 - val_loss: 0.3026 - val_classification_output_loss: 0.3088 - val_segmentation_output_loss: 0.2964 - val_classification_output_acc: 0.9531 - val_segmentation_output_acc: 0.9517 - val_segmentation_output_dice_coef: 0.9490\n",
      "================================================ Saving model ================================================\n",
      "model saved to: shareLayer_Sobel.h5\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"================================================ begin training ================================================\")\n",
    "\n",
    "hist = model.fit([train_x,train_x], \n",
    "                 [train_c_y, train_s_y],\n",
    "                 batch_size=batch_size,\n",
    "                 epochs=200,\n",
    "                 validation_data=([val_x,val_x], [val_c_y, val_s_y]),\n",
    "                 verbose=1,\n",
    "                 callbacks=[reduce_lr, csv_logger],\n",
    "                 shuffle=True)\n",
    "\n",
    "print(\"================================================ Saving model ================================================\")\n",
    "model_filename = \"shareLayer_Sobel.h5\"\n",
    "model.save_weights(model_filename)\n",
    "print('model saved to:', model_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "28078269",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'np' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_10494/2183893224.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mN\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m200\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstyle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"ggplot\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m# plt.plot(N, hist.history[\"loss\"], label=\"train_loss\")\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# plt.plot(N, hist.history[\"classification_output_loss\"], label=\"classification_output_loss\")\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'np' is not defined"
     ]
    }
   ],
   "source": [
    "N = np.arange(0, 200)\n",
    "plt.style.use(\"ggplot\")\n",
    "plt.figure()\n",
    "# plt.plot(N, hist.history[\"loss\"], label=\"train_loss\")\n",
    "# plt.plot(N, hist.history[\"classification_output_loss\"], label=\"classification_output_loss\")\n",
    "# plt.plot(N, hist.history[\"segmentation_output_loss\"], label=\"segmentation_output_loss\")\n",
    "\n",
    "# plt.plot(N, hist.history[\"classification_output_acc\"], label=\"classification_output_acc\")\n",
    "# plt.plot(N, hist.history[\"segmentation_output_acc\"], label=\"segmentation_output_acc\")\n",
    "# plt.plot(N, hist.history[\"segmentation_output_dice_coef\"], label=\"segmentation_output_dice_coef\")\n",
    "\n",
    "plt.plot(N, hist.history[\"val_loss\"], label=\"loss\")\n",
    "plt.plot(N, hist.history[\"val_classification_output_loss\"], label=\"cla_loss\")\n",
    "plt.plot(N, hist.history[\"val_segmentation_output_loss\"], label=\"seg_loss\")\n",
    "\n",
    "plt.plot(N, hist.history[\"val_classification_output_acc\"], label=\"cla_acc\")\n",
    "plt.plot(N, hist.history[\"val_segmentation_output_acc\"], label=\"seg_acc\")\n",
    "plt.plot(N, hist.history[\"val_segmentation_output_dice_coef\"], label=\"Dice\")\n",
    "\n",
    "plt.title(\"Training Loss and Accuracy\")\n",
    "plt.xlabel(\"Epoch #\")\n",
    "plt.ylabel(\"Loss/Accuracy/DSC\")\n",
    "plt.legend()\n",
    "plt.savefig(os.path.join('output/', Name+'.png'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "452674d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------Start predicting------\n",
      "------------------------------------------------ Classification testing ------------------------------------------------\n",
      "                  precision    recall  f1-score   support\n",
      "\n",
      "   bengin_images     0.8571    0.9767    0.9130        43\n",
      "malignant_images     0.9333    0.6667    0.7778        21\n",
      "\n",
      "        accuracy                         0.8750        64\n",
      "       macro avg     0.8952    0.8217    0.8454        64\n",
      "    weighted avg     0.8821    0.8750    0.8687        64\n",
      "\n",
      "------------------------------------------------ Segmentation testing ------------------------------------------------\n",
      "Test total loss: 0.6001038998365402\n",
      "Test classification loss: 0.9678511321544647\n",
      "Test segmentation loss: 0.2323567196726799\n",
      "Test classification accuracy: 0.875\n",
      "Test segmentation accuracy: 0.9539745151996613\n",
      "Test segmentation dice_coef: 0.9520971179008484\n",
      "64/64 [==============================] - 1s 11ms/step\n",
      "AUC: 0.9878973282183112\n",
      "Precision: 0.6899228282008861\n",
      "Recall: 0.6181018014291028\n",
      "m_Iou: 0.48372414708353717\n",
      "F1_score: 0.652040540061794\n"
     ]
    }
   ],
   "source": [
    "print(\"------Start predicting------\")\n",
    "predictions_c, predictions_s = model.predict([test_x, test_x], batch_size=8)\n",
    "print(\"------------------------------------------------ Classification testing ------------------------------------------------\")\n",
    "\n",
    "print(classification_report(test_c_y.argmax(axis=1), predictions_c.argmax(axis=1), target_names=lb.classes_, digits=4))\n",
    "\n",
    "print(\"------------------------------------------------ Segmentation testing ------------------------------------------------\")\n",
    "\n",
    "# evaluate the model\n",
    "# loss = model.evaluate(test_x, [test_c_y, test_s_y], verbose=0)\n",
    "loss, cla_loss, seg_loss, cla_acc, seg_acc, seg_dice_coef = model.evaluate([test_x, test_x], [test_c_y, test_s_y], verbose=0)\n",
    "print('Test total loss:', loss)\n",
    "print('Test classification loss:', cla_loss)\n",
    "print('Test segmentation loss:', seg_loss)\n",
    "\n",
    "print('Test classification accuracy:', cla_acc)\n",
    "print('Test segmentation accuracy:', seg_acc)\n",
    "print('Test segmentation dice_coef:', seg_dice_coef)\n",
    "\n",
    "\n",
    "preds_c, preds_s = model.predict([test_x, test_x], batch_size=8, verbose=1)\n",
    "test_mask = test_s_y.flatten()\n",
    "pred_mask = preds_s.flatten()\n",
    "fpr, tpr, thresholds = roc_curve(test_mask, pred_mask, pos_label=1)\n",
    "roc_auc = auc(fpr, tpr)\n",
    "print(\"AUC:\", roc_auc)\n",
    "\n",
    "# Precision, Recall, accuracy, F1, IoU = p_r_f1_iou(test_s_y, preds_s)\n",
    "# print('Precision:', Precision)\n",
    "# print('Recall:', Recall)\n",
    "# print('m_Iou:', IoU)\n",
    "# print('F1_score:', F1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44af90ae",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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